Efficient resource allocation in dynamic large-scale environments is one of the cha llenges of Grids. In centralized economic-based allocation approaches, the user requests\udcan be matched to the fastest, cheapest or most available resource. This approach,\udhowever, shows limitations in scalability and in dynamic environments. In\udthis paper, we explore a decentralized economic approach for resource allocation in\udGrid markets based on the Catallaxy paradigm. Catallactic agents discover selling\udnodes in the resource and service Grid markets, and negotiate with each other maximizing\udtheir utility by following a strategy. By means of simulations, we evaluate the\udbehavior of the approach, its resource allocation efficiency and its performance with\uddifferent demand loads in a number of Grid density and dynamic environments. Our\udresults indicate that while the decentralized economic approach based on Catallaxy\udapplied to Grid markets shows similar efficiency to a centralized system, its decentralized\udoperation provides greater advantages: scalability to demand and offer, and\udrobustness in dynamic environments.
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